1 Introduction

The growth of Information and Communication Technology (ICT) in different applications is so ascending. Many organizations make a strong effort into applying ICT for providing online services to citizens which leads to creating a new concept as Electronic services or simply E-services. E-service is conceptualized as an organization’s use of ICT for providing faster, more convenient and efficient access to and delivery of information and services to the general population (Abdel-Basset et al. 2018; Verkijika and De Wet 2018a).

Evidence from private and state sectors reveals that many organizations have the willingness to deliver e-services to citizens for decreasing the organization’s cost and enhancing business performance. Fostering user’s satisfaction and trust is considered another key factor for developing e-services such that the vast majority of organizations have set up a website to offer e-services (Al-dweeri et al. 2019; Ali 2019; Zhou et al. 2019).

The development of e-services is an evolutionary process that is comprised of different steps. The preliminary step is creating a website to share services unilaterally. The next step enables users to experience bilateral communication by offering interactive services. Further e-services development steps cause more citizen’s interaction with websites and organizations (Concha et al. 2012; Iannacci et al. 2019; Joshi and Islam 2018).

Website creation is seen as the most fundamental and infrastructural step for developing e-services which allow organizations to deliver values to users, therefore, constant assessment of websites as the main platform for further development of e-services is so significant in providing better quality online services to citizens (Joshi and Islam 2018; Verkijika and De Wet 2018b).

Universities are also no exception in this regard, moreover, they are taken into account as the main hub for propagating science and knowledge in the world, therefore, they are highly expected to deliver high quality e-services to students and researchers (Ismailova and Inal 2018; Singla and Aggarwal 2018).

Due to the high importance of e-services websites to deliver better quality services to people, assessing different dimensions of websites aimed at enhancing e-services quality is so essential (Abdel-Basset et al. 2018; Verkijika and De Wet 2018b). In this paper, a model is proposed for evaluating e-services of university websites which is able to spot the strengths and weaknesses of e-services websites and suggest some useful recommendations for improving website quality.

Assessing and selecting e-services websites with highest readiness is a complex Multi Criteria Decision Making (MCDM) problem with multiple and often conflicting quantitative and qualitative criteria, therefore, Multi Criteria Decision Making methods are seen as a great solution to solve the problem (Abdel-Basset et al. 2018; Burmaoglu and Kazancoglu 2012). MCDM methods enable decision makers to analyze alternatives from various viewpoints given criteria and sub-criteria simultaneously (Asees Awan and Ali 2019; Hatami-Marbini et al. 2013).

The overall structure of the paper is comprised of seven sections. Firstly, the most significant studies of assessing e-services of university websites are recognized and the most effective indexes and indicators are extracted which are able to assess wide and various dimensions of e-services of universities. Secondly, the importance of indexes and indicators is supposed to be obtained. Due to having different indexes and indicators for assessment, hybrid Multi Criteria Decision Making (MCDM) methods are selected for addressing the problem. Two separate MCDM methods such as Analytical Hierarchy Process (AHP) and PROMETHEE are applied for assigning weight and ranking of indexes and indicators respectively. In the next step, a group of experts is selected based on purposive sampling technique to answer a pairwise comparison questionnaire for collecting data then the model is applied for assessing the readiness of 21 top-leading Iranian universities websites whose readiness value is obtained by calculation of index’s and indicator’s readiness value. In the next section, the model is compared and analyzed with previous models. The last section is allocated for the research conclusion.

2 Literature reviews

Over the past years, different studies are conducted for assessing e-services of university websites. Each study considers limited dimensions of e-services websites. Manzoor et al. (2019) proposed a model for assessing and enhancing the usability of university websites. The model considered following criteria such as navigation (ease of use of information access), organization of website (information structure and quality), ease of use (usability), design, communication (contact information) and content. The model criteria can be categorized as usability, content and information quality and website design. The model is applied for assessing 86 university websites of Canada, the US and Europe. The criteria weight is the same and equal to one (Manzoor et al. 2019).

Benaida et al. (2018) assessed the usability of university websites in Arabic countries. The study concentrates on ease of use of e-services which are evaluated by following indexes: user’s willingness to use the website, lack of website complexity (ease of use of information access), ease of use of website, support and maintenance, service integration, uniformity between webpages, fast learnability, website responsiveness, trust and no need for training before using services. The study assessed three top leading university websites of Saudi Arabia and England. In a nutshell, the study indexes can be summarized as usability, support and maintenance, website design, responsiveness quality and trust. Indexes’ weight is the same and equal to one (Benaida et al. 2018).

Faustina and Balaji (2016) conducted a research on assessing Indian university websites. The study considered two main dimensions of responsiveness quality and website design. The study’s indexes are load time, page size, number of items, broken links, response time, page rank, traffic and design optimization. The study assessed the e-services of three university websites in Chennai. The most and the least important indexes are load time (its weight is 0.3) and broken links (its weight is 0.02) (Faustina and Balaji 2016).

Devi and Sharma (2016) assessed the e-services of Indian university websites. The study concentrated on the effectiveness of e-services websites (while the previous model focused on responsiveness quality and website design). The study considered the following indexes: functionality (searching tools), usability (ease of use of services), reliability (usability), presentation (visual beauty and technical features of the website) and content and information quality. The study indexes can be summarized as usability, website design and content and information quality. The most and the least important indexes are content and information quality and usability (its weight is 0.3) and presentation and reliability (its weight is 0.1) respectively (Devi and Sharma 2016).

Zhou et al. carried out a study on assessing Chinese university libraries’ websites. The study consists of the following indexes: content, website design, practicability (usability), maintenance and expansion (technical features of websites). The research indexes can be categorized as content and information quality, usability, support and maintenance and website design. The most and the least important indexes are as content and information quality (its weight is 0.416) and expansion (its weight is 0.059) (Zhou et al. 2013).

Hasan (2013) assessed the usability of Jordanian university websites. The model is comprised of following indexes such as navigation, website architecture, ease of use and communication (usability), website design (visual beauty) and content and information quality. The indexes’ weight is the same and equal to one (Hasan 2013).

Alotaibi (2013) conducted a study on assessing the usability of Saudi Arabian university websites. The study considered following indexes such as visual design and consistency, links and navigation, data entry form, information and precision, privacy and security, search functionality, error tolerance and help and feedback. The indexes can be summarized as website design, usability, content and information quality, security, services and support and maintenance. The indexes’ weight is the same and equal to one (Alotaibi 2013).

Table 1 shows the previous studies title and indexes of each one:

Table 1 E-services of university websites assessment studies
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As shown in Table 1, each study considered various dimensions of university websites. The most important and effective indexes for assessing university websites are website design, usability, content and information quality, support and maintenance, responsiveness quality, services, trust and security. Chart 1 shows the frequency of indexes in previous studies:

Since one of the most important missions of e-services development is increasing citizen participation in organizational decisions and processes, therefore, citizen participation should be considered as one of the most important indexes for assessing e-services of university websites (Porumbescu 2016; Twizeyimana and Andersson 2019; Verkijika and De Wet 2018b). The index is not considered in any previous studies of university websites assessment. The index intends to assess the presence of online facilities and services for boosting up citizens’ involvement with organizational decisions and processes. Online surveys, online complaints, Frequent Answer and Questions (FAQ) are the most common indicators for measuring the index. There are also other indicators such as online weekly meeting and online polling which help enhance citizen participation with organizational decisions.

Given Chart 1 and the above explanation, the most effective indexes for assessing e-services of university websites are website design, trust, security, support and maintenance, participation, usability, services, responsiveness quality and content and information quality.

3 Proposed Model’s indexes for assessing E-services of university websites

Considering section 2, The most important and effective indexes for assessing e-services of university websites are as website design, responsiveness quality, security, trust, content and information quality, participation, support and maintenance, services and usability which are considered as proposed model’s indexes. The indexes and relevant indicators are introduced and explained separately:

  1. a.

    Website design

The index is comprised of two dimensions such as visual beauty and technical features of the website. Visual beauty assesses the uniformity of webpages through considering color, font and design. Technical features of the website consider the website compatibility with different web browsers and systems. Offering personalized services based on users’ requirements is also taken into account (Manzoor et al. 2019; Rasyid and Alfina 2017; Tella 2019).

  1. b.

    Responsiveness quality

The index assesses the speed of website responsiveness to user’s requests. The index is assessed by following indicators such as server responsiveness after each click and required time for downloading files and documents. Deploying servers inside the country and applying wide bandwidth for transferring information between servers and user’s browsers make a strong contribution to enhancing website responsiveness. With the rapid development and popularity of social media among the general population, website compatibility with social media can leverage website responsiveness to user’s requests (Rasyid and Alfina 2017; Twizeyimana and Andersson 2019; Verkijika and De Wet 2018b).

  1. c.

    Security

Website security is assessed in two dimensions of backend and frontend. The backend mostly evaluates the required facilities for providing a secure platform for transferring information between the user’s browser and servers. It is evaluated by the following indicators: the use of secure protocols such as SSL and HTTPS as well as data encryption between server and user’s browser in order to avoid data leakage. The frontend aspect examines required facilities on User Interface (UI) such as security code image, virtual keyboard and sending alarm message when an anonymous user penetrates into the user’s account (Henriksson et al. 2007; Rasyid and Alfina 2017; Verkijika and De Wet 2018b).

  1. d.

    Trust

The index assesses people’s trust in organizations and deliver e-services. It is comprised of three main aspects of risk, characteristics of state agencies and social characteristics of citizens. The first aspect concentrates on keeping the personal information of users confidential by avoiding sharing them with organizations and abusers. The second aspect is divided into two parts such as an organization’s credibility and user’s past experience. The first part assesses an organization’s honesty in delivering e-services to citizens as well as considering citizens’ interest in offered online services. The second part mostly considers user’s feedback about the quality of e-services such as effectiveness and user satisfaction in the past experience. Social characteristics of users assess citizen’s inclination and willingness to trust the third party. Additionally, citizen’s nodding acquaintance with the internet is also another indicator. The presence of an organization’s logo on all web pages and displaying completion messages can increase a user’s trust in organization and e-services (Alzahrani et al. 2017, 2018; Benaida et al. 2018).

  1. e.

    Content and information quality

The Index assesses precision, accuracy and update of information. Additionally, displaying the last date of website updating can inform citizens regarding information updates. Due to different software for viewing information on a website, presenting information with different formats such as HTML and PDF helps enhance information quality (Huang and Benyoucef 2014; Rasyid and Alfina 2017; Verkijika and De Wet 2018a, b).

  1. f.

    Participation

The index examines existed facilities on a website for increasing citizen’s participation with organizations. The most critical facilities are as: online surveys, online criticism and complaints and providing a space on the webpage to share questions and receive answers (FAQ). Holding online meeting for keeping citizens informed about the latest changes in offered e-services is another indicator which leads to broader citizen’s participation (Tella 2019; Twizeyimana and Andersson 2019; Verkijika and De Wet 2018a, b) .

  1. g.

    Support and maintenance

Required facilities for guiding users aimed at better use of online services and systems are assessed by support and maintenance. Online support and maintenance and website user manual facilitate the use of delivered online services. Sending emails for informing users about the last status of their requests and displaying error messages while doing transactions with the website are also considered (Sivaji et al. 2011; Verkijika and De Wet 2018a; Pena-Lopez 2018).

  1. h.

    Services

The index assesses the number of delivered e-services on a website. The most fundamental services are included as downloadable forms and online financial transaction which enable users to pay bills without referring to office. Online tender documents and online tender participation are other pivotal delivered e-services (Benaida et al. 2018; Verkijika and De Wet 2018a, b).

  1. i.

    Usability

The Index recognizes the existed facilities for ease of use of websites and e-services. Having a search engine, simple menu and website map helps users reach information and e-services faster and more conveniently. Returnability and ability to cancel ongoing transactions facilitate the use of e-services and websites. Supporting different languages makes the websites and e-services more applicable to users regardless of nationality (Ismailova and Kimsanova 2017; Manzoor et al. 2019).

Table 2 indicates the indexes and indicators of the proposed model:

Table 2 Indexes and indicators of the proposed model
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As shown in Table 2, the most effective indexes and indicators for assessing the e-services of university websites are determined. Given that the indexes and indicators are able to evaluate wider dimensions of e-services websites in comparison with previous studies therefore the final assessment results are more precise and reliable.

4 Research methodology

After extracting the most important indexes and indicators for assessing e-services websites, a model is supposed to reveal for assessing the readiness of e-services websites. Selecting and ranking e-services websites based on indexes and indicators is a Multi Criteria Decision Making (MCDM) problem, therefore, MCDM methods are proposed for determining the preference and importance of indexes and indicators (Abdel-Basset et al. 2018; Burmaoglu and Kazancoglu 2012).

A number of MCDM methods have been developed to solve multi criteria decision making problems such as AHP, ANP, PROEMTHEE, VIKOR and, etc. (Abdel-Basset et al. 2018; Abdulah et al. 2019). In this research Analytical Hierarchy Process (AHP) method is selected for assigning weight to the indexes. AHP is a reliable method that is able to decompose complicated multi criteria decision making problems into a pairwise comparison between indexes and assign weight and rank them (Singh et al. 2018).

As the number of indicators is plentiful, AHP method is not highly recommended for ranking indicators. Instead, PROEMTHEE method is suggested for ranking indicators. PROEMTHEE is an outranking method that is able to rank indicators regardless of their dependency and frequency (Singh et al. 2018).

In this research AHP and PROEMTHEE methods are applied for assigning weight and ranking indexes and indicators respectively. The methods are explained in details:

4.1 AHP

AHP method was firstly proposed by Thomas Satty in 1970 (Wang et al. 2019). The method is able to convert complicated decision making problems into the simple pairwise comparison between indexes therefore the method has received high attention and popularity by researchers. The method is comprised of five steps (Carfora et al. 2016; Darko et al. 2019; Konstantinos et al. 2019; Zyoud et al. 2016):

  1. a.

    Decision matrix

Firstly, indexes are compared pairwisely using linguistic variables presented in Table 3 then the results are put into a decision matrix:

Table 3 Linguistic variables conversion into Likert number
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$$ {A}_{n\times n}=\left[\begin{array}{ccc}1& \cdots & {a}_{1n}\\ {}{a}_{21}& 1& \vdots \\ {}\vdots & {a}_{ij}& \vdots \\ {}{a}_{n1}& \cdots & 1\end{array}\right] $$
(1)

Where the decision matrix A, aij displays comparison value between index i to index j for all indexes i, j ∊ {1, 2, …, n}. n shows the number of indexes in the problem.

  1. b.

    Data Aggregation

Since a pairwise comparison questionnaire is distributed between 80 experts selected based on purposive sampling technique for data collection, data aggregation is required to turn expert’s judgments into a single decision matrix:

$$ {a}_{ij}=\frac{\sum_{l=1}^n{a}_{ij}^l}{n} $$
(2)

Where aij represents the pairwise comparison value between index i and j in the single decision matrix. n shows the number of experts.

  1. c.

    Normalization

The normalized decision matrix is obtained by the division of each element value over the addition of relevant column value:

$$ {\overset{\acute{\mkern6mu}}{a}}_{n1}=\frac{a_{n1}}{\sum_{l=1}^n{a}_{l1}} $$
(3)
  1. d.

    Calculation of Indexes weight

Weight of each index is obtained by:

$$ \boldsymbol{W}={\left[{w}_1,{w}_2,\dots, {w}_n\right]}^T $$
(4)
$$ {A}_{n\times n}=\left[\begin{array}{ccc}{\overset{\acute{\mkern6mu}}{a}}_{11}& \cdots & {\overset{\acute{\mkern6mu}}{a}}_{1n}\\ {}{\overset{\acute{\mkern6mu}}{a}}_{21}& {\overset{\acute{\mkern6mu}}{a}}_{22}& \vdots \\ {}\vdots & {\overset{\acute{\mkern6mu}}{a}}_{ij}& \vdots \\ {}{\overset{\acute{\mkern6mu}}{a}}_{n1}& \cdots & {\overset{\acute{\mkern6mu}}{a}}_{nn}\end{array}\right]\left\{\begin{array}{c}{Z}_1={\overset{\acute{\mkern6mu}}{a}}_{11}+{\overset{\acute{\mkern6mu}}{a}}_{12}+\dots +{\overset{\acute{\mkern6mu}}{a}}_{1n}\\ {}{Z}_2={\overset{\acute{\mkern6mu}}{a}}_{21}+{\overset{\acute{\mkern6mu}}{a}}_{22}+\dots +{\overset{\acute{\mkern6mu}}{a}}_{2n}\\ {}\vdots \\ {}{Z}_n={\overset{\acute{\mkern6mu}}{a}}_{n1}+{\overset{\acute{\mkern6mu}}{a}}_{n2}+\dots +{\overset{\acute{\mkern6mu}}{a}}_{nn}\end{array}\right. $$
(5)
$$ {Z}_t={Z}_1+{Z}_2+\dots +{Z}_n $$
(6)
$$ {W}_1=\frac{Z_1}{Z_t},{W}_2=\frac{Z_2}{Z_t},\dots, {W}_n=\frac{Z_n}{Z_t} $$
(7)

Where Z1 displays the addition of all elements in each row. Zt shows the addition of all elements in the normalized decision matrix. The final weight of each index is obtained by dividing the addition of each row by the addition of all elements in the normalized decision matrix.

  1. e.

    Consistency ratio

The consistency ratio of the decision matrix is obtained by:

$$ CR=\frac{CI}{RI} $$
(8)

Given the above equation, CI is obtained by eq. 5 and RI is obtained by Table 4:

$$ CI=\frac{\lambda_{max}-n}{n-1} $$
(9)
Table 4 Value of (RI)
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n shows the number of indexes. Maximum of eigenvector λmax is obtained by:

$$ {\lambda}_{max}=\frac{1}{n}{\sum}_{i=1}^n\frac{(AW)_i}{w_i} $$
(10)

The value of CR should be less than 0.1 to reach a consistent decision matrix.

4.2 PROEMTHEE

PROMETHEE is firstly proposed by Brans in 1986. PROEMTHEE is considered an outranking method. Ease of use and high precision in ranking alternatives cause many researchers to apply PROEMTHEE method in research activities. The method has different versions but PROMETHE II is applied for providing complete indicator’s ranking. The method is comprised of 6 steps (Abdulah et al. 2019; Wu et al. 2019):

  1. a.

    Decision Matrix

Firstly, each indicator is compared pairwisely with other indicators using linguistic variables presented in Table 4 then the results are put into the decision matrix.

  1. b.

    Data aggregation

A pairwise comparison questionnaire is distributed between 80 experts selected based on a purposive sampling technique. Collected data is aggregated and put into a single decision matrix by:

$$ {a}_{ij}=\frac{\sum_{l=1}^n{a}_{ij}^l}{n} $$
(11)
  1. c.

    Calculation of indexes deviation

The Difference between two indicators evaluation value is calculated by:

$$ d\left(a,b\right)={g}_j(a)-{g}_j(b) $$
(12)

gj(a) and gj(b) represent pairwise comparison value of a and b indicators respectively. d(a, b) denotes difference value between the evaluation of a and b indicators.

  1. d.

    Calculation of indicators preferences respecting each index

Indicators preference respecting to each index is obtained by:

$$ {P}_j\left(a,b\right)={F}_j\left[{d}_j\left(a,b\right)\right] $$
(13)

Pj denotes preference of indicator a to indicator b respecting index j which is obtained by calculation of preference function F.The most popular preference function are as: usual, U-shape, V-shape, level, linear and Gaussian. Due to the common use of V-shape preference function in previous research, it is applied for spotting precise preference of indicators.

(14)

d shows the difference value of two indicators respecting to each index. Additionally, q and p show indifference and preference threshold. The lower value of the preference function shows the indifference of decision makers. On the contrary, a higher value indicates a stronger preference.

  1. e.

    Calculation of index preference respecting to all indexes

In this step, indicator preference is calculated respecting to all indexes by:

$$ \pi \left(a,b\right)={\sum}_{j=1}^k{P}_j\left(a,b\right)\times {w}_j $$
(15)

w displays index weight. Pj(a, b) represents preference indicator a to b respecting to index j. π(a, b) shows the preference degree of indicator a to indicator b respecting all indexes.

  1. f.

    Calculation of preference order

In this step, indicators ranking can be conducted partially or completely but in this research complete ranking is required to compare all indicators simultaneously while in partial ranking the preference of all indicators is not comparable. The complete preference order of indicators is obtained by:

$$ {\varnothing}^{+}=\frac{1}{n-1}{\sum}_{x\in A}\pi \left(a,x\right) $$
(16)
$$ {\varnothing}^{-}=\frac{1}{n-1}{\sum}_{x\in A}\pi \left(x,a\right) $$
(17)
$$ \varnothing ={\varnothing}^{+}-{\varnothing}^{-} $$
(18)

∅+ is the positive outranking flow or known as leaving flow denoting how indicator a dominates all other indicators. ∅− is the negative outranking flow or entering flow indicating how indicator a is dominated by all other indicators. n shows the number of indicators.

∅ is net flow which is obtained by difference of positive and negative flow values. The net flow allows all indicators to be comparable. The higher value of net flow denotes a higher preference of indicator.

5 Proposed model for assessing e-services websites of Iranian universities

The main objective of the research is proposing an extended model for assessing the readiness of e-services of university websites. The model is able to recognize strengths and weaknesses of e-services websites as well as offering some useful recommendations for enhancing website quality. The model’s research methodology consists of two main steps, the first step is responsible for assigning weight to indexes using Analytical Hierarchy Process (AHP) and the second step is devoted to ranking indicators by PROEMTHEE method. Figure 1 shows the research methodology steps:

Fig. 1
figure 1

Research methodology steps

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A pairwise comparison questionnaire was distributed between 80 experts in the sphere of Information Technology and e-services to assess indexes and indicators pairwisely. The respondents are selected based on a purposive sampling technique. In the purposive sampling technique, respondents are determined by researchers. The researcher requires to have prior knowledge about the purpose of the study so that they can properly choose eligible respondents (Karabatak and Polat 2019). Table 5 shows demographic information of respondents:

Table 5 Demographic information of respondents
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Table 6 shows the final results of the proposed model where all indexes and indicators are assigned weigh and ranked by AHP and PROMETHEE methods respectively:

Table 6 Indexes weight and indicators ranking of the proposed model
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As shown in Table 6, the most important indexes are as: security (its weight is equal to 0.1570), trust (its weight is equal to 0.1410), responsiveness quality (its weight is equal to 0.1250), content and information quality (its weight is equal to 0.1240), website design (its weight is equal to 0.1017), support and maintenance (its weight is equal to 0.0930), usability (its weight is equal to 0.0901), services (its weight is equal to 0.0880) and participation (its weight is equal to 0.0835).

6 Assessing the readiness of e-services of top-leading Iranian university websites

The proposed model is applied for assessing the readiness of e-services of 21 outstanding Iranian university websites such as Tehran university, Tehran university of medical science, Sharif university of technology, Amirkabir university of technology, Tarbiat Modares university, Shahid Beheshti University of medical sciences and health services, Isfahan university of technology, Iran University of science and technology, Ferdowsi Mashhad University, Shahid Beheshti University, Shiraz University, Tabriz University, Shiraz University of medical sciences, K.N Toosi University of technology, Alzahra University, Kharazmi University, Allameh Tabatabai University, Iran University of medical sciences, Ahvaz University of medical sciences, Tabriz University of medical sciences and Mashhad University of medical science. In order to quantify the study, the readiness value of indicators is obtained by selecting a number between zero to 100. The higher value denotes the higher readiness of indicator. Table 7 shows the general information of the universities (UniRank 2019):

Table 7 General information of universities
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  1. 1.1.

    Security

Security is considered the most important index. The index is comprised of two main dimensions such as security at infrastructure and user interface. The first dimension is looking for providing a secure platform for transferring data between servers and the user’s browser by applying secure protocols (such as HTTPS and SSL) and data encryption. The second dimension evaluates required facilities at User Interface (UI) such as security code image, a virtual keyboard for entering a password and sending alarm message when an unknown user logs into other user’s accounts. Figure 2 shows the readiness value of indicators:

Fig. 2
figure 2

Readiness of security indicators

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The most important indicators are SSL and HTTPS which pave the way for more secure data transferring between the user’s browser and servers. They are all well-considered on the websites and data are transferred securely but user interface indicators such as a virtual keyboard and security code image are not well-observed such that less than 40% of indicators exist on the websites. The final readiness value of the security index is equal to 55%.

6.1 Trust

The second most important index is trust which is responsible for assessing user’s trust in organization and e-services. The index is comprised of three main dimensions such as risk, social characteristics of citizens and state agencies’ characteristics. The state agency characteristics are divided into two parts such as an organization’s credibility which is assessed by the following indicators: considering citizen’s interest and organization’s honesty in delivering e-services to citizens. The second part is users’ past experience which is evaluated by the user’s satisfaction with and effectiveness of e-services. Risk dimension assesses transaction speed, financial transaction errors and user’s privacy (avoidance of sharing user’s personal information with third parties). Social characteristic of citizen’s dimension is comprised of following indicators such as user’s knowledge about the internet and their willingness to trust the third party. Figure 3 shows the readiness value of indicators:

Fig. 3
figure 3

Readiness of trust indicators

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Considering citizen’s interest is the most important indicator such that less than 30% of students and users take the view that universities consider their interest in delivered e-services while the vast majority of students believe that universities are honest in e-services. Findings show that less than 30% of students are satisfied with e-services in the past experience. The effectiveness and efficiency of e-services play a crucial role in enhancing citizen’s trust. The assessment indicates that only 50% of citizens believe that e-services of university websites are efficient and effective. As the vast majority of university websites users are students, they have knowledge about how to access the internet, therefore. Its readiness value is 100%. A huge volume of user’s personal information is kept on the websites. It is highly expected from universities to keep them confidential and avoid sharing them with other organizations and unknown people whose readiness value is obtained 100% indicating that user’s personal information is not at risk of disseminating with abusers and other organizations.

The absence of financial transaction errors on the website also makes a contribution to increasing user’s trust which is well-considered and users can do financial transactions with the least errors. User’s willingness to trust the other party is mostly relevant to social and cultural characteristics. The indicator is not in suitable status such that just half of the users are inclined to trust the third party. Having a logo on web pages and displaying completion message is also well-considered on all of the websites. The final readiness value of the trust index is equal to 74%.

6.2 Responsiveness quality

Responsiveness quality assesses website responsiveness to user’s requests on the website. The index is comprised of two parts such as infrastructure and user interface (UI). Website infrastructure assesses the speed of website response after each click. Applying wide bandwidth plays an important role in raising data transfer speed between the user’s browser and servers, moreover, it allows more users to access websites concurrently. Using low-size files and pictures can enhance website response to user’s requests. Due to the rapid development of social networks among the general population, website compatibility with social networks can increase the website’s response to meet more user’s requests. Figure 4 shows the readiness value of indicators:

Fig. 4
figure 4

Readiness of responsiveness quality indicators

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The most important indicators are website response after each click and required time for downloading documents that are not well-assessed and only half of the websites enjoy satisfactory response time. Low-size files and pictures are observed in more than 90% of websites. Social network compatibility is so pivotal to meeting online user’s requests. Findings show that only half of the websites are equipped with social networks. The final readiness value of the responsiveness quality index is equal to 72%.

6.3 Content and information quality

The index assesses the information quality based on precision, accuracy and update of information. Presenting information with different formats allows users to have easy access to information. Presenting Information in a simple language without any complexity and ambiguities is another important indicator for leveraging information quality. Figure 5 shows the readiness value of indicators:

Fig. 5
figure 5

Readiness of content and information quality indicators

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The most important indicator is information precision which is considered in 75% of websites. Information accuracy and updating are other important indicators that are considered in more than 50% of websites. Presenting information based on user’s requirements is so crucial whose readiness value obtained around 40%. Since users use different software for viewing information, presenting information by different formats such as PDF and HTML facilitates information access which is considered in less than 20% of websites. Displaying the last date of website update is observed in less than 40% of the websites. The final readiness value of content and information quality index is equal to 67%.

6.4 Website design

The index is comprised of two main dimensions such as visual beauty and technical features of website. The visual beauty is responsible for assessing the uniformity of web pages such as color, font and the same design. The indicators make the websites more appealing and attractive to users. The technical features of the website are assessed by website compatibility with different systems and browsers. Figure 6 shows the readiness value of indicators:

Fig. 6
figure 6

Readiness status of website design indicators

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The vast majority of websites consider the most important indicators such as website compatibility with browsers and systems. Since the websites allow students to take credit for each semester, therefore, presenting personalized e-services is provided such that more than 80% of websites are equipped with. Page title, simple pictures, font and personalized information registration is considered in more than 80% of the websites. Using the same font and simple design is just observed in more than 50% of the websites which intends to decrease websites’ attractiveness and integrity. The final readiness value of the website design index is equal to 79%.

6.5 Support and maintenance

The index assesses existed facilities such as online support and maintenance and website user manual for guiding people aimed at better use of e-services. Other indicators intend to keep users informed regarding the status of online requests such as sending tracking numbers and sending informative emails to users about the last status of requests. Figure 7 shows the readiness value of indicators:

Fig. 7
figure 7

Readiness of support and maintenance indicators

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The most important indicator is online support which helps users experience a better use of the website. The indicator is considered in less than 50% of websites. Online maintenance is also another indicator that is observed in less than 20% of websites. Sending emails for informing users regarding their requests is poor-considered and only 4% of websites are equipped with. The final readiness value of support and maintenance index is equal to 30%.

6.6 Usability

The index assesses required facilities for ease of use of websites and e-services which take place through a search engine, simple menus and a website map. Ability to cancel process and return to previous step during transaction facilitates the use of websites and e-services. Figure 8 shows the readiness value of indicators:

Fig. 8
figure 8

Readiness of usability indicators

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The vast majority of websites (more than 80%) consider the most important indicators such as accessibility, simple menus and search engines. Website map plays a crucial role in directing users to reach information and e-services conveniently which is observed in 50% of the websites. Link management assesses the activation of links for connecting to other web pages and websites. Findings indicate that 20% of links are broken therefore the readiness value of the indicator is 80%. The final readiness value of the usability index is equal to 72%.

6.7 Services

The index assesses the variety and number of delivered services. The most important services are downloadable forms, downloadable tender documents and online financial transactions. The Number of specialized e-services for students and researchers is another indicator. Figure 9 shows the readiness value of services indicators:

Fig. 9
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Readiness of services indicators

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Downloadable forms is one of the most important indicators whose readiness value is 92%. Downloadable tender documents and online tender participation enable users to participate in tender easily which are assessed below the par and their readiness values are less than 20%. Financial truncation is so helpful for users to experience online payment which is existed in all the websites. The final readiness value of the services index is equal to 51%.

6.8 Participation

Since one of the main objectives of e-services development is increasing user’s participation in organizational decisions and processes. The index evaluates the presence of facilities for increasing user’s transactions with the organization and website. The indicators assess facilities for enabling users to leave comments and suggestions such as online survey, frequent questions and answers (FAQ), online complaints and online criticism. Other relevant indicators are online weekly newsletters and online meetings for informing users about the latest delivered e-services. Other indicators assess the required information to contact an organization such as email and number. Figure 10 shows the readiness value of indicators:

Fig. 10
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Readiness of participation indicators

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The most three important indicators are online complaints and criticism, frequent answers and questions and online surveys. The finding show that they are considered in less than half of the websites. Online voting and online meeting aimed at collecting users’ comments in the organization’s decisions and informing users can leverage user’s participation whose readiness value is zero such that they do not exist in any websites. The final readiness value of the participation index is equal to 41%.

The index readiness value is obtained by calculating the average readiness value of relevant indicators. Table 8 and Figure 11 shows the readiness value of indexes in e-services of university websites:

Table 8 Readiness value of indexes
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Fig. 11
figure 11

Readiness status of indexes

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Table 9 shows the readiness value of indexes on university websites. The readiness value of each website can be obtained by the addition of multiplication of indexes’ weight into average indicators’ readiness value which is shown in Table 8. The readiness value of university websites is a number between zero and one. The higher value denotes the higher readiness of websites.

Table 9 Readiness value of top-leading Iranian university websites
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As shown in Table 9, the readiness value of 21 outstanding university websites is obtained and ranked. Higher value indicates the higher readiness. The final result shows that Tarbiat Modares University and Amirkabir University received the highest and lowest readiness respectively.

7 Discussion

The purpose of this paper is proposing an extended model for assessing the e-services of university websites. The model is able to assess the readiness value of e-services websites as well as recognizing weaknesses and strengthens. The model is comprised of nine indexes such as security, trust, content and information quality, responsiveness quality, website design, participation, support and maintenance, services and usability and relevant indicators for measuring indexes.

Since the e-services development is different in countries, therefore proposing a comprehensive model being compatible with all countries is impossible therefore previous studies have conducted their research on a specific territory. Manzoor et al. (2019) suggested a model for e-services of university websites in the US, Europe and Canada. Benaida et al. (2018) conducted a study for evaluating Arabic university websites. Faustina and Balaji (2016) carried out a research on assessing the quality of Indian university websites. Previous studies show that each model is context-based and suitable for a specific country and cannot be applied for other territories. Consequently, having a model for assessing Iranian e-services of university websites is essential to be designed.

In this study 9 indexes are taken into account for assessing the readiness of e-services websites while previous studies considered the limited number of indexes. Manzoor et al. (2019) mostly focused on usability of university websites. Benaida et al. (2018) considered wider aspects of e-services websites by considering following indexes trust, support and maintenance, website design and usability. Faustina and Balaji (2016) concentrated on website responsiveness and website design. Additionally, one of the main objectives of e-services is increasing people’s involvement in organizational activities and processes, however, none of the previous studies have taken participation index into account. The proposed model is comprised of more various indexes and indicators which is able to provide more precise and accurate result in comparison with previous studies.

Assessing and ranking the readiness of e-services websites are conducted based on conflicting qualitative and quantitative indexes and indicators which is seen as a Multi Criteria Decision Making (MCDM) problem (Abdel-Basset et al. 2018; Burmaoglu and Kazancoglu 2012). The preference and importance of extracted indexes and indicators are obtained by MCDM methods. The indexes are assigned a weight by AHP method and indicators are ranked using PROEMTHEE method. The preference of indexes are obtained as: security, trust, responsiveness quality, content and information quality, website design, support and maintenance, usability, services and participation.

The extended model is proposed for assessing e-services of Iranian university websites. The Iranian e-services development is medium (ranked as 86th country in the world) (Pena-Lopez 2018). The preference ranking of indexes shows that infrastructural indexes (such as security, trust, responsiveness quality and content and information quality) receive higher weight comparing to other indexes which assess the ease of use of websites and citizen’s involvement(such as participation, support and maintenance, services and usability). The final result of the model is supported by Asian countries whose e-services developments are similar to Iran’s. Table 10 indicates the preference of indexes in different countries and continents:

Table 10 Preference of Infrastructural indexes in previous studies
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As shown in Table 10, the infrastructural indexes received better raking and higher weight in Chinese, Asian and Indian countries whose e-services development are close to Iran (Pena-Lopez 2018).

The model assigned lower weight to the indexes which assess the citizen’s involvement and ease of use of websites such as services, support and maintenance, participation and usability. The Asian and Chinese studies supported the research result which is shown in Table 11:

Table 11 Preference of participation and ease of use of websites indexes in previous studies
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Findings show that the preference of citizen’s involvement and ease of use of websites indexes are less important than infrastructural indexes in Chinese studies whose e-services development is similar to Iran’s. On the flip side, the situation is different in more developed countries such as Australia. The importance of infrastructural indexes are less evaluated while ease of use of websites and citizen’s involvement receive higher preference.

8 Conclusion

In this paper, an extended model is proposed for assessing the readiness of e-services of university websites. The most influential and relevant studies with the title of university website assessment are reviewed. The most important indexes and indicators are extracted from previous studies that are capable of evaluating various dimensions of e-services websites. Assessing e-services website is a Multi Criteria Decision Making problem so the extracted indexes and indicators are assigned weight and ranked by hybrid MCDM methods such as AHP and PROEMTHEE methods respectively. A pairwise comparison questionnaire was disseminated between 80 experts in the sphere of e-services and Information Technology (IT) to assess indexes and indicators. The experts are selected based on a purposive sampling technique. The most important indexes are obtained as security, trust, content and information quality, responsiveness quality, website design, participation, support and maintenance, services and usability. Finally, the model was applied for assessing the readiness of 21 top-leading Iranian university websites. The final result shows that Tabiat Modares and Amirkabir university websites have the highest and lowest readiness respectively.